Modeling Life Cycle Energy Consumption And Greenhouse Gas Emissions For High-speed Railways

As a rapid intercity public transit mode with large capacity, the high-speed railway (HSR) is expected to mitigate the contradiction between the numerous population and inadequate resources per capita in China. As a result, the HSR construction has accelerated significantly with the support of national policies in recent years. However, the infrastructure construction of the HSR involves a large amount of engineering quantity and the high-speed train (HST) also consumes high electricity to run. In addition, in China the infrastructure of bridges and culverts is built extensively along the HSR to replace the at-grade foundation. Besides China has a dominate ratio of low efficiency and high emissions coal-based electricity in generation, which is why the environmental impact of the HSR in China needs to be reexamined in the perspective of a life cycle.To achieve the above-referred goals, of all the environmental impacts, the research focuses on energy consumption (EC) for and greenhouse gas (GHG) emissions from the HSR. Based on the characteristics of the life cycle EC of and GHG emissions from the passenger transport of the HSR, an analysis frame and measuring approach is presented to assess the EC and GHG emissions due to the infrastructure construction of the HSR. On account of the mechanical work, a numerical model is proposed to calculate the traction electricity requirement for the running of HST, which is a primary activity in the operation phase of the HSR. The abilities of saving. energy and reducing GHG emissions of the HSR are reappraised from the perspective of a life cycle. Finally, parts of energy-saving transport organization schemes of the HSR are raised for application. The main contents and conclusions of the dissertation are as follows.(1) The life cycle of the HSR is divided into five elementary phases including the conception, construction, operation, maintenance and disposal, where representative activities are illustrated. The characteristics of the life cycle EC of and GHG emissions from the passenger transport of the HSR consists of two aspects. On one hand, the operation phase of the HSR where energy requirements of its typical activities are highly dependent on the electricity does not usually cause GHG emissions, whereas they are transferred into the process of the electricity generation. On the other hand, as a result of building the large-scale infrastructure, a noticeable ratio of the life cycle EC of and GHG emissions from the HSR is hidden in the construction phase. Worldwide, the life cycle assessment of the HSRs has an obvious regional characteristic. The construction and operation phase are confirmed as the dominating phases for the EC and GHG emissions in the life cycle of the HSR, yet the proportions for the two phases are distinguishing in a different region.(2) The HSR line is split into five sub-models:bridge and culvert, tunnel, at-grade foundation, track as well as electrification system. Combined with the regional inventory of product data, the EC and GHG emissions due to the infrastructure construction of the HSR are estimated via evaluating the building materials requirements and equipment use of the five sub-models. The application of the approach in the Beijing-Shanghai HSR demonstrates the EC resulting from building its infrastructure reaches145,502TJ, while the GHG emissions are19,154Kt CO2-equivalent. Moreover,90%of the EC and GHG emissions are both from the use of building materials. Of all the five sub-models, the tunnel construction on a per-km basis consumes the most energy and emits the most GHG, which are respectively1.9and1.7times of the second place that is the bridge and culvert construction. Even so, the bridge and culvert construction of the Beijing-Shanghai HSR contributes67%of the EC and66%of the GHG emissions in view of the fact that its proportion of bridges and culverts is up to86%. Cement and steel have significant impacts on the GHG emissions from the HSR infrastructure construction. The GHG emissions are expected to be reduced by13%and7%respectively following a20%decrease of the carbon intensity for the cement and steel production.(3) A numerical model is proposed to estimate the traction electricity requirement for the running of HSTs via a calculation of mechanical work. The model is capable to manage the situation that the stopping section is too short to achieve the preliminarily set target speed for the HST. Besides, with an introduction of the transmission efficiency of the engines, the model is also effective in a certain level of accuracy requirements even lack of the traction force curve or the current curve of the HST. The application of the model indicates that the target speed influences the traction electricity consumption of the HST by acting on the peak speed it might accelerate to. Regarding the target speed raised from200to350km/h, the elasticity for the traction electricity consumption about the target speed is1.8to2.1approximately for all the stop schedules. The impact of the stopping times of the HST on its traction electricity consumption is expressed by the acceleration cycles, and the traction electricity requirement for an all-stop HST is around1.7times of that for a through HST while running on an HSR with a length of169km and9passenger stations totally.(4) The Monte Carlo Method is adopted to assess the abilities of the HSR in saving energy and reducing GHG emissions with the introduction of the probability theory. The triangular distribution describes the uncertainty of the EC intensities and load factors of passenger transport modes as well as the life cycle EC and GHG emission factors of fuels, including electricity. The uniform distribution is used regarding to the uncertainty of the shifted ratios of HSR passengers from other transport modes. Moreover, a R. Pearl growth curve is employed to fit the development of the HSR passengers. Consequently, the volume and probability of the HSR in saving energy and reducing GHG emissions yearly in the operation phase is assessed, and the recuperation times after operating for the EC and GHG emissions due to the construction and maintenance of the HSR infrastructure is also assessed. The assessment demonstrates that the ability of the HSR in saving energy is still strong examined from the perspective of the life cycle while its ability in reducing GHG emissions has some uncertainty and is not as strong as its ability in saving energy. As expected, the life cycle GHG emission intensity of the electricity, the load factor of the HSR and the ratios of the shifted and induced passengers of the HSR are all significant contributors to the ability of the HSR in reducing GHG emissions.(5) The speed optimization model of the HST is proposed considering its traction electricity. The transport organization scheme becomes an effective measure to improve the environmental benefits of the HSR after the line has been constructed and the HST has been selected. The objectives of the optimization model are the maximum profits for the HSR transport section and the minimum generalized travel cost for the HSR passengers. The speed has an influence on the cost of the HSR transport section by affecting the traction electricity requirement of the HST, and on the income by competing for the passengers with the bus and private car. Restrained by the transport supply, the departure and arrival time of the HSTs and the number of the HSTs, a multi-objective nonlinear model for the speed optimization is established, which is solved by the application of the algorithm based on fuzzy compromise programming. The results show that under a certain level of economic development, the HST with an ultrahigh speed is not able to reduce the generalized cost of passengers choosing the HSR, but result in a significant increase in electricity requirements for moving.